Langchain Example Updates (#199)

examples/langchain/langchainpy-localai-example/full_demo.py

@@ -1,4 +1,6 @@
 import os
+import logging
+
 from langchain.chat_models import ChatOpenAI
 from langchain import PromptTemplate, LLMChain
 from langchain.prompts.chat import (
@@ -13,6 +15,9 @@ from langchain.schema import (
     SystemMessage
 )
 
+# This logging incantation makes it easy to see that you're actually reaching your LocalAI instance rather than OpenAI.
+logging.basicConfig(level=logging.DEBUG)
+
 print('Langchain + LocalAI PYTHON Tests')
 
 base_path = os.environ.get('OPENAI_API_BASE', 'http://api:8080/v1')
@@ -24,7 +29,7 @@ chat = ChatOpenAI(temperature=0, openai_api_base=base_path, openai_api_key=key,
 
 print("Created ChatOpenAI for ", chat.model_name)
 
-template = "You are a helpful assistant that translates {input_language} to {output_language}."
+template = "You are a helpful assistant that translates {input_language} to {output_language}. The next message will be a sentence in {input_language}. Respond ONLY with the translation in {output_language}. Do not respond in {input_language}!"
 system_message_prompt = SystemMessagePromptTemplate.from_template(template)
 human_template = "{text}"
 human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)
@@ -34,6 +39,8 @@ chat_prompt = ChatPromptTemplate.from_messages([system_message_prompt, human_mes
 print("ABOUT to execute")
 
 # get a chat completion from the formatted messages
-chat(chat_prompt.format_prompt(input_language="English", output_language="French", text="I love programming.").to_messages())
+response = chat(chat_prompt.format_prompt(input_language="English", output_language="French", text="I love programming.").to_messages())
+
+print(response)
 
 print(".");